Mathematical Biology

Research into the development and application of state-of-the-art mathematical/statistical tools and techniques to investigate biological processes and systems. This area includes research into the development of such tools for the mathematical treatment of biological processes operating at any spatial or temporal scale, or over multiple scales, from the molecular level to the whole-population level.

Research using mature or well-established mathematical/statistical methodologies to investigate biological processes and systems is not included and will instead be supported under other relevant parts of the EPSRC portfolio, or by the Biotechnology and Biological Sciences Research Council (BBSRC), Medical Research Council (MRC) or Natural Environment Research Council (NERC), depending on the nature of the research.

Over the last decade, the drive towards increasingly quantitative descriptions of systems and processes in the life sciences has stimulated demand for innovative mathematical and statistical tools and techniques to tackle biological and biomedical challenges. This strategy aims to maintain the size of the research area as a proportion of the EPSRC portfolio, to ensure that the UK has an appropriate research and skills base to respond to demand while delivering mathematically excellent research.

By the end of the Delivery Plan period, we aim to have:

  • Established, with funders in the life sciences (e.g. BBSRC and MRC), a complementary approach to developing trained researchers with interdisciplinary skills at the interface of life and mathematical sciences
  • Developed a sustainable portfolio of research into the development of novel mathematical and statistical techniques for biological modelling, prediction and analysis in healthcare, building on the critical mass established by the Centres for Mathematical Sciences in Healthcare, and which contributes to the delivery of key EPSRC Ambitions
  • Encouraged increased collaboration and integration between statisticians and mathematicians working at the interface with the life sciences, and to have stimulated improved links between Mathematical Biology and areas of the mathematical sciences beyond traditional applied mathematics (e.g. Complexity Science, Geometry and Topology, Mathematical Analysis, and Statistics and Applied Probability). Researchers are encouraged to take advantage of mathematical sciences infrastructure to facilitate development of new collaborations
  • Enhanced Mathematical Biology’s impact by encouraging closer links with other relevant areas of engineering and the physical sciences (e.g. Biological Informatics, Biophysics and Soft Matter Physics and Synthetic Biology) and by promoting knowledge exchange between mathematical sciences, life sciences and end-users (including industry)

Mathematical Biology in the UK is internationally excellent. The UK is a major contributor to the discipline, alongside the US and other parts of Europe. The community’s strength has been recognised through numerous awards and prizes, both nationally and internationally (Evidence source 1,2,3).

The importance of Mathematical Biology stems from its contribution to the life and medical sciences, with mathematical modelling highlighted in the Maxwell review that assessed the importance of engineering and physical sciences to health and life sciences (Evidence source 4). In the longer term, advanced mathematical tools and techniques are expected to be critical to key UK industries, including pharmaceuticals and biotechnology (Evidence source 1,2,3,5).

Evidence from the Research Excellence Framework (REF) 2014 exercise suggests that overall researcher numbers working wholly or primarily in Mathematical Biology increased significantly over the previous Delivery Plan period. (Evidence source 6). There is some concern, however, around the supply of new researchers with the appropriate interdisciplinary skills to be successful in this area (Evidence source 2,7). The BBSRC and MRC review of vulnerable skills identified that mathematics, statistics and computational biology skills were lacking among researchers from a life sciences background, increasing demand for mathematically trained researchers with skills at the interface with the life sciences (Evidence source 7). Conversely, over the last Delivery Plan, EPSRC has supported a number of Centres for Doctoral Training (CDTs) with at least some relevance to the area and Mathematical Biology currently draws the third-largest training budget of all mathematical sciences research areas.

The area is relevant to the following Healthy, Resilient and Productive Ambitions:

H3: Optimise diagnosis and treatment

This research area will enable more systematic treatment of uncertainty in complex biological models, and of underpinning mathematical approaches to challenges in biophysics and bioengineering.

H4: Develop future therapeutic technologies

This area will use mathematical pharmacology-based approaches to improve drug discovery and delivery.

R1: Develop better solutions to acute threats: cyber, defence, financial and health

This area will deliver improvements in mathematical techniques for modelling and understanding health pandemics.

P1: Introduce the next generation of innovative and disruptive technologies

Advanced mathematical modelling will enable the use of biological processes in new ways.

Research area connections

This diagram shows the top 10 connections between Research Areas within the EPSRC research portfolio. The depth of the segment relates to value of grants and the width of the segment relates to the number of grants shared by those two Research Areas. Please click to see the related Research Area rationale.


We aim to maintain this area as a proportion of the EPSRC portfolio.

Visualising our Portfolio (VoP)
Visualising our portfolio (VoP) is a tool for users to visually interact with the EPSRC portfolio and data relationships.

EPSRC support by research area in Mathematical biology (GoW)
Search EPSRC's research and training grants.

Contact Details

In the following table, contact information relevant to the page. The first column is for visual reference only. Data is in the right column.

Name: Mike Ward
Job title: Portfolio Manager
Organisation: EPSRC
Telephone: 01793 444196